Do Transformer Attention Heads Provide Transparency in Abstractive
Summarization?

Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?

1 July 2019

Maartje ter Hoeve

Maarten de Rijke

Papers citing "Do Transformer Attention Heads Provide Transparency in Abstractive Summarization?"

9 / 9 papers shown

Title
Towards explainable evaluation of language models on the semantic similarity of visual concepts Maria Lymperaiou George Manoliadis Orfeas Menis Mastromichalakis Edmund Dervakos Giorgos Stamou AAML 24 5 0 08 Sep 2022
Diagnosing AI Explanation Methods with Folk Concepts of Behavior Alon Jacovi Jasmijn Bastings Sebastian Gehrmann Yoav Goldberg Katja Filippova 41 15 0 27 Jan 2022
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks Thorben Funke Megha Khosla Mandeep Rathee Avishek Anand FAtt 28 38 0 18 May 2021
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness? Alon Jacovi Yoav Goldberg XAI 48 571 0 07 Apr 2020
On Identifiability in Transformers Gino Brunner Yang Liu Damian Pascual Oliver Richter Massimiliano Ciaramita Roger Wattenhofer ViT 30 187 0 12 Aug 2019
OpenNMT: Open-Source Toolkit for Neural Machine Translation Guillaume Klein Yoon Kim Yuntian Deng Jean Senellart Alexander M. Rush 273 1,896 0 10 Jan 2017
Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu M. Schuster Zhehuai Chen Quoc V. Le Mohammad Norouzi ... Alex Rudnick Oriol Vinyals G. Corrado Macduff Hughes J. Dean AIMat 718 6,750 0 26 Sep 2016
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 220 7,930 0 17 Aug 2015